Industry 4.0: An innovative manufacturing process on a Digital Twin Application

Authors

DOI:

https://doi.org/10.53591/easi.v2i1.2176

Keywords:

Industry 4.0, Digital Transformation, Micro-Manufacturing, Single Edge Micro-Cutting, Cyber-physical systems

Abstract

The fourth industrial revolution requires the process equipment to work together through the strategy of cyber-physical systems. This project aims to contribute to this revolution by presenting a tool and methodology for creating cyber-physical systems. A V-model was used for the design process, in which the digital twin of a 3PRS+XY+C machine tool was developed. It started by defining the requirements, the basis for creating the logical-functional structure. This structure was the guide for completing the behavioural models of each element, the cascade control, and the 3D design of the machine. The simulation was carried out with the digital twin ready to verify the correct operation. A position and speed test were performed with step start and a second order signal showing proper control and compliance with the setpoint. The tests performed show that the strategy used allowed the realisation of the digital twin that conforms to the cyber-physical system of the machine. Also, due to the design mode, the model is highly flexible, and its modular structure facilitates the changes. It is the right time to apply this strategy in the Ecuadorian industry and thus reduce the technological gap and increase international competitiveness.

Author Biographies

Marcelo Fajardo-Pruna, Faculty of Mechanical Engineering and Production Sciences, Escuela Superior Politécnica del Litoral. Guayaquil, Ecuador.

Doctor en Ingeniería Mecánica con intereses en la integración de varios campos de la ingeniería, tales como; inteligencia artificial, redes neuronales, visión artificial, robótica colaborativa, gestión de la vida del producto e industria 4.0, para la mejora de productos, mecanismos y sistemas en la industria y la I+D de soluciones de ingeniería mediante el uso de CAD/CAM/CAE y validación experimental.

Luis Lopez-Estrada, Department of Mechanical Engineering, Universidad Politécnica de Madrid. Madrid, Spain, 28006.

Ingeniero Mecatrónico (2005). Tecnológico de Monterrey, México. Ph.D. en Ingeniería Mecánica (2019), Universidad Politécnica de Madrid, España. Investigador en el Departamento de Ingeniería Mecánica, Universidad Politécnica de Madrid. Áreas de experticia: Industria 4.0, Micromecanizado, Fabricación Avanzada, Visión Artificial.

Daniela Sanchez-Orosco, Faculty of Mechanical Engineering and Production Sciences, Escuela Superior Politécnica del Litoral. Guayaquil, Ecuador.

Estudiante de Ingeniería Mecatrónica con competencias en robótica e industria 4.0. Su enfoque principal son las aplicaciones de navegación autónoma, inteligencia artificial y mecatrónica para diseñar máquinas y dispositivos robóticos. En Industria 4.0, sus intereses se centran en los sistemas de simulación y comunicaciones con el objetivo de desarrollar gemelos digitales y su integración en la fabricación inteligente.

Christian Tutiven, Faculty of Mechanical Engineering and Production Sciences, Escuela Superior Politécnica del Litoral. Guayaquil, Ecuador.

La carrera académica de Christian Tutivén comenzó en 2009 como profesor de tiempo parcial en los cursos de Instrumentación y Automática en la Facultad de Ingeniería Técnica de la Universidad Católica Santiago de Guayaquil (UCSG). Cuatro años más tarde, inicia sus estudios en el programa de doctorado de Automática, robótica y visión de la Universidad Politécnica de Cataluña (UPC). Obtuvo su doctorado en 2018, donde hizo una presentación sobre diagnóstico de fallas y estrategias de control tolerante a fallas para turbinas eólicas. Actualmente, es profesor e investigador en la Escuela Superior Politécnica del Litoral (ESPOL), donde actualmente es tutor de 10 alumnos que está aplicando diferentes técnicas (redes LSTM, redes GRU, redes híbridas, gemelos digitales, redes siamesas, etc.). ) para monitorear la salud estructural de las turbinas eólicas. Además, imparte el curso Deep Learning en la Universidad de Nariño.

Giovanny Pillajo-Quijia, Research and Innovation Coordination, Asociación de Becarios del Ecuador (ABREC). Ecuador

Ingeniero Mecánico (2009). Escuela Politécnica Nacional, Ecuador. Ph.D. en Ingeniería de Producción y Diseño Industrial (2022), Universidad Politécnica de Madrid, España. Investigador en el Departamento de Coordinación de Investigación e Innovación ABREC, Ecuador. Áreas de experticia: Seguridad Vehicular, Inteligencia Artificial, Diseño Mecánico e Ingeniería del Transporte

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Published

2023-07-29

How to Cite

Fajardo-Pruna, M., Lopez-Estrada, L., Sanchez-Orosco, D., Tutiven, C., & Pillajo-Quijia, G. (2023). Industry 4.0: An innovative manufacturing process on a Digital Twin Application. EASI: Engineering and Applied Sciences in Industry, 2(1), 1–10. https://doi.org/10.53591/easi.v2i1.2176

Issue

Vol. 2 No. 1 (2023): Applications in Education and Sustainability Management in Industry 4.0 (January-June Issue)

Section

Research articles

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Copyright (c) 2023 Marcelo Fajardo-Pruna, Luis Lopez-Estrada, Daniela Sanchez-Orosco, Christian Tutiven, Giovanny Pillajo-Quijia

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